unconstrained optimization - определение. Что такое unconstrained optimization
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Что (кто) такое unconstrained optimization - определение

WAY OF EXPLORING REACTION PATHS IN COMPUTATIONAL CHEMISTRY
Geometry optimization; Energy minimization (energy optimization)

Quadratic unconstrained binary optimization         
COMBINATORIAL OPTIMIZATION PROBLEM
Unconstrained binary quadratic programming; UBQP
Quadratic unconstrained binary optimization (QUBO), also known as unconstrained binary quadratic programming (UBQP), is a combinatorial optimization problem with a wide range of applications from finance and economics to machine learning. QUBO is an NP hard problem, and for many classical problems from theoretical computer science, like maximum cut, graph coloring and the partition problem, embeddings into QUBO have been formulated.
Constrained optimization         
IN FINANCE, LINEAR PROGRAMMING, ECONOMICS AND COST MODELING
Constrained optimization problem; Constraint optimization; Maratos effect; Soft constraint; Hard constraint; Algorithms for solving constrained optimization problems; Methods for solving constrained optimization problems; Constrained minimisation; Constrained minimization
In mathematical optimization, constrained optimization (in some contexts called constraint optimization) is the process of optimizing an objective function with respect to some variables in the presence of constraints on those variables. The objective function is either a cost function or energy function, which is to be minimized, or a reward function or utility function, which is to be maximized.
Price optimization         
USE OF PRICING METHODS TO MAXIMIZE THE PURCHASING BEHAVIOR OF CONSUMERS
Price optimization software
Price optimization is the use of mathematical analysis by a company to determine how customers will respond to different prices for its products and services through different channels. It is also used to determine the prices that the company determines will best meet its objectives such as maximizing operating profit.

Википедия

Energy minimization

In the field of computational chemistry, energy minimization (also called energy optimization, geometry minimization, or geometry optimization) is the process of finding an arrangement in space of a collection of atoms where, according to some computational model of chemical bonding, the net inter-atomic force on each atom is acceptably close to zero and the position on the potential energy surface (PES) is a stationary point (described later). The collection of atoms might be a single molecule, an ion, a condensed phase, a transition state or even a collection of any of these. The computational model of chemical bonding might, for example, be quantum mechanics.

As an example, when optimizing the geometry of a water molecule, one aims to obtain the hydrogen-oxygen bond lengths and the hydrogen-oxygen-hydrogen bond angle which minimize the forces that would otherwise be pulling atoms together or pushing them apart.

The motivation for performing a geometry optimization is the physical significance of the obtained structure: optimized structures often correspond to a substance as it is found in nature and the geometry of such a structure can be used in a variety of experimental and theoretical investigations in the fields of chemical structure, thermodynamics, chemical kinetics, spectroscopy and others.

Typically, but not always, the process seeks to find the geometry of a particular arrangement of the atoms that represents a local or global energy minimum. Instead of searching for global energy minimum, it might be desirable to optimize to a transition state, that is, a saddle point on the potential energy surface. Additionally, certain coordinates (such as a chemical bond length) might be fixed during the optimization.